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A Markov Chain Monte Carlo multiple imputation procedure for dealing with item nonresponse in the German SAVE survey

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  • Schunk, Daniel

Abstract

Important empirical information on household behavior is obtained from surveys. However, various interdependent factors that can only be controlled to a limited extent lead to unit and item nonresponse, and missing data on certain items is a frequent source of difficulties in statistical practice. This paper presents the theoretical underpinnings of a Markov Chain Monte Carlo multiple imputation procedure and applies this procedure to a socio-economic survey of German households, the SAVE survey. I discuss convergence properties and results of the iterative multiple imputation method and I compare them briefly with other imputation approaches. Concerning missing data in the SAVE survey, the results suggest that item nonresponse is not occurring randomly but is related to the included covariates. The analysis further indicates that there might be differences in the character of nonresponse across asset types. Concerning the methodology of imputation, the paper underlines that it would be of particular interest to apply different imputation methods to the same dataset and to compare the findings.

Suggested Citation

  • Schunk, Daniel, 2007. "A Markov Chain Monte Carlo multiple imputation procedure for dealing with item nonresponse in the German SAVE survey," Papers 07-06, Sonderforschungsbreich 504.
  • Handle: RePEc:mnh:spaper:2561
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    References listed on IDEAS

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    1. Daniel Schunk, 2008. "A Markov chain Monte Carlo algorithm for multiple imputation in large surveys," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 101-114, February.
    2. Cristina Barceló, 2006. "Imputation of the 2002 wave of the Spanish survey of household finances (EFF)," Occasional Papers 0603, Banco de España;Occasional Papers Homepage.
    3. Scheuren, Fritz, 1988. "Missing-Data Adjustments in Large Surveys: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 298-299, July.
    4. Lothar Essig & Joachim K. Winter, 2009. "Item Non-Response to Financial Questions in Household Surveys: An Experimental Study of Interviewer and Mode Effects," Fiscal Studies, Institute for Fiscal Studies, vol. 30(Special I), pages 367-390, December.
    5. Daniel Schunk, 2006. "The German SAVE Survey: Documentation and Methodology," MEA discussion paper series 06109, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    6. Hersch, Joni, 2000. "Gender, Income Levels, and the Demand for Cigarettes," Journal of Risk and Uncertainty, Springer, vol. 21(2-3), pages 263-282, November.
    7. Joni Hersch & W. Kip Viscusi, 1990. "Cigarette Smoking, Seatbelt Use, and Differences in Wage-Risk Tradeoffs," Journal of Human Resources, University of Wisconsin Press, vol. 25(2), pages 202-227.
    8. Sande, I G, 1988. "Missing-Data Adjustments in Large Surveys: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 296-297, July.
    9. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 300-301, July.
    10. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 287-296, July.
    11. Phillip B. Levine & Tara A. Gustafson & Ann D. Velenchik, 1997. "More Bad News for Smokers? The Effects of Cigarette Smoking on Wages," ILR Review, Cornell University, ILR School, vol. 50(3), pages 493-509, April.
    12. Susanne Rässler & Regina Riphahn, 2006. "Survey item nonresponse and its treatment," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 217-232, March.
    13. Phillip B. Levine & Tara A. Gustafson & Ann D. Velenchik, 1995. "More Bad News for Smokers? The Effects of Cigarette Smoking on Labor Market Outcomes," NBER Working Papers 5270, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Michael Ziegelmeyer, 2013. "Illuminate the unknown: evaluation of imputation procedures based on the SAVE survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(1), pages 49-76, January.
    2. Daniel Schunk, 2008. "A Markov chain Monte Carlo algorithm for multiple imputation in large surveys," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 101-114, February.

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